-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
386 lines (364 loc) · 45.9 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
<!DOCTYPE HTML>
<!--
Dimension by HTML5 UP
html5up.net | @ajlkn
Free for personal and commercial use under the CCA 3.0 license (html5up.net/license)
-->
<html>
<head>
<title>Katarzyna Ostapowicz</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no" />
<link rel="stylesheet" href="assets/css/main.css" />
<noscript><link rel="stylesheet" href="assets/css/noscript.css" /></noscript>
</head>
<body class="is-preload">
<!-- Wrapper -->
<div id="wrapper">
<!-- Header -->
<header id="header">
<div class="logo">
<span class="images/KO_small.jpg" alt=""></span>
</div>
<div class="content">
<div class="inner">
<h1>Katarzyna Ostapowicz</h1>
<p>Researcher at the Norwegian Institute for Nature Research</p>
</div>
</div>
<nav>
<ul>
<li><a href="#About">About</a></li>
<li><a href="#Education">Education</a></li>
<li><a href="#Projects">Projects</a></li>
<li><a href="#Publications">Publications</a></li>
<!-- <li><a href="#Data&codes">Data&codes</a></li> -->
<li><a href="#Contact">Contact</a></li>
</ul>
</nav>
<ul class="icons">
<li><a href="https://github.com/kasiaostapowicz" class="icon brands fa-github"><span class="label">GitHub</span></a></li>
<li><a href="mailto:katarzyna.ostapowicz@nina.no" class="icon fa-envelope"><span class="label">Email</span></a></li>
</ul>
</header>
<!-- Main -->
<div id="main">
<!-- About -->
<article id="About">
<h3>Katarzyna Ostapowicz</h3>
<h2 class="major">About</h2>
<span class="image main"><img src="images/image_about.jpg" alt="" /></span>
<p></p>
<p>I am currently a researcher at <a href="https://www.nina.no/english/About-NINA/Contact/Employees/Employee-info?AnsattID=16669"><b>the Norwegian Institute for Nature Research NINA</b></a>. As a researcher specialized in remote sensing, land system science, and landscape ecology, my motivation centers on using technological advancements to tackle ecological challenges. With ecosystems playing a crucial role in climate regulation and biodiversity support, my work aims to bridge the gap in their effective monitoring, management, and restoration. This is particularly urgent in the face of rapid urbanization and environmental change, where my focus is on integrating remote sensing with ecological knowledge to better understand and safeguard terrestrial and marine ecosystems. My goal is to contribute to innovative, practical solutions for sustainable environmental management and policy-making. I am a strong advocate of open science and reproducible research. </p>
<p></p>
<button><a href="https://www.linkedin.com/in/katarzyna-ostapowicz-2a41593/">Profesional expirience</a></button>
<p></p>
</article>
<!-- Education -->
<article id="Education">
<h3><a href="#About">Katarzyna Ostapowicz</a></h3>
<h2 class="major">Education</h2>
<span class="image main"><img src="images/image_education.jpg" alt="" /></span>
<p></p>
<h4><i class='fas'></i> 2007: PhD in the Earth Science within Geography</h4>
<p><b>Faculty of Biology and Earth Science, Jagiellonian University (Poland)</b></br>
<b>Thesis:</b> Spatiotemporal simulation of land cover change dynamics (<em>Institute of Geography and Spatial Management at the Jagiellonian University Award for outstanding PhD thesis within Geography defended between 2005 and 2007</em>)</p>
<p></p>
<h4><i class='fas'></i> 2004: MSc in Physics (specialization: Nuclear Physics)</h4>
<p><b>Institute of Physics, Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University (Poland)</b><br/>
<b>Thesis:</b> Cross-sections of nucleus-proton fragmentation reactions</p>
<p></p>
<h4><i class='fas'></i> 2002: MSc in Physical Geography within Environmental and Mathematical Studies (specialization: Geographic Information Systems)</h4>
<p><b>Institute of Geography and Spatial Management, Faculty of Biology and Earth Science, Jagiellonian University (Poland)</b><br/>
<b>Thesis:</b> Spatial distribution of forests in the Western Beskidy Mountains (<em>Polish Geographical Society Award for outstanding MSc thesis</em>)</p>
<p></p>
<h4><i class='fas'></i> 2001-2002: Pedagogical training</h4>
<p><b>Teacher Training Center, Jagiellonian University (Poland)</b></p>
<p></p>
<h3>Certificates</h3>
<h4><i class='fas'></i> 2018: UAVO qualification certificate</h4>
<p><b>Civil Aviation Authority, Poland</b></p>
<p></p>
</article>
<!-- Projects -->
<article id="Projects">
<h3><a href="#About">Katarzyna Ostapowicz</a></h3>
<h2 class="major">Projects</h2>
<span class="image main"><img src="images/image_running_projects_1.jpg" alt="" /></span>
<h4>POLARSIF Project: Assessing Vegetation Phenological Changes in Polar Regions Using Solar Induced Fluorescence Data (2024) [role: Principal Investigator, SATS project] </h4>
<p>The POLARSIF project, a pioneering initiative focusing on the Arctic vegetation of Svalbard from 2019 to 2023, utilizes Solar Induced Fluorescence (SIF) to monitor and analyze vegetation phenological changes under the impact of climate change. This project represents a significant advancement in remote sensing technologies, specifically by employing the direct measurement capabilities of SIF over traditional methods such as the Normalized Difference Vegetation Index (NDVI). SIF's sensitivity to environmental changes provides more accurate data in high-latitude regions, making it particularly effective in areas like Svalbard, where vegetation is highly responsive to climate variability. The project aims to enhance our understanding of how Arctic vegetation adapts to shifting temperature and precipitation patterns, snow cover alterations, and other climatic factors. By correlating these environmental variables with SIF data, the initiative seeks to offer insights into the direct and indirect effects of climate change on Arctic ecosystems. This approach not only contributes to scientific research but also aids in developing effective climate change mitigation strategies by providing data critical for preserving Arctic biodiversity and informing policy decisions.</p>
<p></p>
<h4>ARCVEG project: Arctic tundra vegetation as a mirror for landscape response to climate change (2022-2024) [role: Principal Investigator, internal project] </h4>
<p>The rapidly changing landscapes of polar regions, such as Svalbard, present a fascinating yet critical focus for scientific research. Our project takes a deep dive into this icy realm, employing advanced remote sensing technologies to unravel the dynamics of vegetation productivity. By analyzing a suite of satellite imagery—ranging from MODIS and OCO-2 to Sentinel 5P and Sentinel 2—we're piecing together a detailed picture of how vegetation cover in these extreme environments is shifting. This analysis is further enriched by ground-level data, such as FLoX measurements, offering a unique perspective that bridges the gap between space-based observations and on-the-ground reality. The implications of our findings extend far beyond the icy borders of Svalbard. By understanding these shifts in vegetation cover, we're gaining crucial insights into the broader impacts on global carbon cycles and biodiversity. This research not only sheds light on the immediate effects of environmental change in polar regions but also contributes to our understanding of global ecological balances and their susceptibility to climate change.</p>
<p></p>
<h4><a href="#TRACE_project">TRACE project</a>: Trajectories, causes and effects of land cover and land use changes in Central Europe (<a href="https://glp.earth/how-we-work/contributing-projects/trajectories-causes-and-effects-land-cover-and-land-use-changes">Global Land Programme</a> contributing project, grant from <a href="https://www.ncn.gov.pl/?language=en">the National Science Center - Poland</a>, 2019-2023, no.2018/29/B/ST10/02979) [role: Principal Investigator] </h4>
<p>The primary objectives of this project are: (1) to leverage recent advancements in remote sensing for comprehensive mapping of land cover and land use changes, utilizing both optical and radar imagery to capitalize on data-rich time series across Central Europe (Czechia, Hungary, Poland, and Slovakia) spanning the past fifty years; (2) to gain a deeper understanding of the driving factors behind these land cover and land use changes in Central Europe; and (3) to evaluate the impact of these changes on biodiversity, as well as carbon pools and fluxes, throughout the region.</p>
<p></p>
<button><a href="#Completed_projects">Completed projects ...</a></button>
<p></p>
</article>
<!-- TRACE project -->
<article id="TRACE_project">
<h2 class="major">TRACE project</h2>
<h3>Trajectories, causes and effects of land cover and land use changes in Central Europe</h3>
<span class="image main"><img src="images/animation_trace.gif" alt="" /><em>Annual MODIS NDVI with inter-annual compositing (from 2020-01-01 to 2021-01-01)</em></span>
<p></p>
<h3>Background</h3>
<p>Land provides essential resources to society, including food, fuel, fibres and many other ecosystem services that support production functions, regulate risks of natural hazards, or provide cultural and spiritual services. By using the land, society modifies the provision of these services. Changes in land systems are the main factors of global environmental change and, at the same time, have significant consequences for the local environment and human well-being. Understanding and modelling of complex land systems and land change trajectories, the enhanced human pressures on the earth's limited land resources, as well as the increasingly complex drivers of those changes, have been critical objectives for land change science or land system science (LSS).</p>
<p>Central Europe has experienced drastic changes in political, economic, and societal structures since 1990. The shift from centralised command economies to market-oriented systems has altered economic opportunities, induced technological changes and fostered rapid demographic processes. In 2004, economic and political conditions changed significantly for some Central and Eastern European countries with their accession to the European Union. Socio-economic and political boundary conditions constitute the framework for land use decisions, and the system change in Central and Eastern Europe had a substantial impact on land management </p>
<p>Land cover change in Central and Eastern Europe are only summarised in a few studies. Therefore, we focus our project on methodologies that enable us to detect and estimate land cover and land use changes, causes and consequences. </p>
<h3>Project aims and objectives</h3>
<p></p>
<p>The major aims and objectives of the TRACE project include:</p>
<p><b>Mapping and Analysis of Land Cover and Land Use Change Trajectories (Task 1)</b>: Employing remote sensing, the project aimed to map land cover and land use changes across Central Europe (Czechia, Hungary, Poland, Slovakia) over the past fifty years, focusing on processes such as agricultural area abandonment and the wildland-urban interface. This involved utilizing optical and radar imagery, along with data-dense time series, to create a detailed spatial database of these
changes. </p>
<p><b>Understanding the Causes of Changes (Task 2)</b>: Through ensemble modeling techniques and the telecoupling framework, the project seeked to explore the socio-economic, political, and institutional drivers behind these land changes. We achived the goal of understand the why behind land cover and land use modifications, incorporating various datasets to support the analysis in regional scale.</p>
<p><b>Assessing the Effects on Biodiversity and Carbon Cycles (Task 3 and 4)</b>: Another objective was to evaluate how land cover and land use changes have affected biodiversity and carbon pools and fluxes across the region. This involved using remote sensing data and methodologies to analyze the impacts of these changes, providing insights into the consequences for ecosystem services and carbon dynamics. We focused on developmented on indecieced that allowed to improved assessment of biodiversity changes in regional scale - Central Europe but also added additional aspect to our analysis and focus on roadless areas.</p>
<p>The TRACE project directly aligns with several United Nations Sustainable Development Goals (UN SDGs), particularly:
<ul>
<li><b>SDG 13 (Climate Action)</b>: By examining the impact of land use changes on carbon cycles and contributing to knowledge on climate change mitigation through land management.</li>
<li><b>SDG 15 (Life on Land)</b>: The project's focus on biodiversity and ecosystem services relates directly to efforts to protect, restore, and promote sustainable use of terrestrial ecosystems.</li>
<li><b>SDG 11 (Sustainable Cities and Communities)</b>: Through its investigation of the wildland-urban interface, the project contributes to understanding and managing urban expansion in a sustainable manner.</li>
</ul>
</p>
<p>By aiming to provide a comprehensive assessment of land cover and land use changes, their drivers, and their environmental impacts, TRACE supports the broader goals of sustainable development by informing policy and management strategies to balance economic development with environmental conservation and resilience to climate change.</p>
<p></p>
<h3>Publications</h3>
<p></p>
<p><b>Hoffmann M.T., Ostapowicz K.</b>, Bartoń K., Ibisch P.L., Selva N., 2024, Mapping roadless areas in regions with contrasting human footprint, <a href="https://www.nature.com/articles/s41598-024-55283-3">Scientific Reports</a>, 14, 4722, https://doi.org/10.1038/s41598-024-55283-3 </p>
<p><b>Szczęch M</b>; Kania M.; Loch J.; <b>Ostapowicz K.</b>; Struś P., 2024, Mapping grasslands' preservation potential: A case study from the northern Carpathians, <a href="https://onlinelibrary.wiley.com/doi/10.1002/ldr.4941?af=R">Land Degradation & Development</a>, 35, 2, https://doi.org/10.1002/ldr.4941 </p>
<p></p>
<p>More coming soon by the end of 2024</p>
<p></p>
<h3>Team</h3>
<p>Katarzyna Ostapowicz (Principal Investigator)</br>
Mateusz Szczęch (Postdoctoral researcher)</br>
Konrad Turlej (Postdoctoral researcher)</br>
Monika Hoffmann (Doctoral researcher)</br> Aleksandra Wasik (Master student)</p>
<p></p>
<h3>Collaboration</h3>
<p><a href="https://luclab.berkeley.edu/about/"><b>LUC Lab</b></a>, <a href="https://ourenvironment.berkeley.edu/">Department of Environmental Science, Policy, and Management</a>, <a href="https://www.berkeley.edu/">University of California, Berkeley, USA</a></br>
<a href="https://www.iop.krakow.pl/"><b>Institute of Nature Conservation</b>, Polish Academy of Science</a>, Poland</p>
<p></p>
<h3>Acknowledgment</h3>
<li><a href="https://glp.earth/how-we-work/contributing-projects/trajectories-causes-and-effects-land-cover-and-land-use-changes">Global Land Programme</a> contributing project</li>
<li>Grant from <a href="https://www.ncn.gov.pl/?language=en">the National Science Center - Poland</a> (2019-2023, no.2018/29/B/ST10/02979)</li>
<p></p>
<button><a href="#Projects">Running projects ...</a></button>
<p></p>
</article>
<!-- Completed projects -->
<article id="Completed_projects">
<h3><a href="#About">Katarzyna Ostapowicz</a></h3>
<h2 class="major">Completed projects</h2>
<span class="image main"><img src="images/image_projects.jpg" alt="" /></span>
<p></p>
<h4><a href="#SOCPIX_project">SOCPIX project</a>: Socializing the pixel - detecting and understanding of changing land systems with remote sensing and social sciences (grant from <a href="https://nawa.gov.pl/en/nawa">the Polish National Agency for Academic Exchange</a>, 2019-2020, no. PPN/BEK/2018/1/00310/00001) [role: Principal Investigator]</h4>
<p>This project aimed to develop concepts and methodologies to (1) integrate remote sensing data required in telecoupling frameworks with socioeconomic information at the pixel level (PIXEL SOCIALIZATION); (2) accurately map and link land use intensification and expansion, displacement, and transition using remote sensing and spatial data; (3) understand how land use changes are driven by complex factors that transcend spatial, institutional, and temporal scales; and (4) examine how various stakeholders organize land use dynamics, influencing regime shifts in land systems and the emergence of frontiers.</p>
<p></p>
<h4><a href="#RS4FOR_project">RS4FOR project:</a> Forest change detection and monitoring using passive and active remote sensing data (grant from <a href="https://www.ncn.gov.pl/?language=en">the National Science Center - Poland</a>, 2016-2020, no.2015/19/B/ST10/02127) [role: Principal Investigator] </h4>
<p>The main aim of the RS4FOR project was to develop and test approaches that allow improving forest cover change detection and monitoring using different types of remote sensing data (optical data: Landsat 4, 5, 7, 8 (data time series from 1985 to 2017) and Sentinel 2 (data time series from 2015-17), radar data: Sentinel 1 (data time series from 2014-17), and data from airborne laser scanning (ALS) (2013, project ISOK). We focused on both forest cover conversion and modification and three different aspects of forest monitoring: (1) forest cover and its change, (2) prediction models of forest structure and its change and (3) forest health. Our approaches was developed for the temperate forest in mountainous areas.</p>
<p></p>
<h4>Use of UAV data for agriculture land abandonment and forest secondary succession mapping (grant from the Faculty of Geography and Geology at the Jagiellonian University - fund for linking science with practice, 2019, No.) [role: Principal Investigator] </h4>
<p>This project developed an innovative workflow using unmanned aerial vehicles (UAVs) and machine learning techniques to automatically detect agricultural land abandonment and map forest secondary succession. By employing high-resolution UAV imagery, the project captured detailed visual data across various landscapes, enhancing the precision of ecological monitoring. Advanced machine learning algorithms were tailored to analyze this data, identifying patterns of land use change and natural regrowth effectively. The resulting automated system offers critical insights into land management, facilitating real-time decision-making and policy development. This approach not only streamlines the monitoring processes but also provides scalable solutions for managing ecological recovery and optimizing land use. The project's findings are crucial for informing sustainable land management strategies and conservation efforts, highlighting the transformative potential of integrating UAV technology with artificial intelligence in environmental science.</p>
<p></p>
<h4><a href="https://ruj.uj.edu.pl/xmlui/bitstream/handle/item/66508/ostapowicz_pazur_lachowski_international_workshop_on_ecological_connectivity_modelling_2018.pdf?sequence=1&isAllowed=y">CON@SK.PL project:</a> Transboundary ecological connectivity – modelling landscapes and ecological flows (grant from <a href="https://www.visegradfund.org/">the Visegrad Funds</a>, 2017-2018, No. 21640051) [role: Co-Principal Investigator]</h4>
<p>The CON@SK.PL project was dedicated to gaining a deeper understanding of habitat connectivity in the Northern Carpathians of Slovakia and Poland. Our international team focused on assessing multispecies connectivity, specifically for the brown bear (Ursus arctos) and European bison (Bison bonasus L.). Utilizing state-of-the-art approaches, we were able to make substantial contributions to addressing critical conservation issues concerning these species.</p>
<p></p>
<h4><a href="#LIM_project">LIM project:</a> Integration of categorical- and gradient-based approaches in landscape fragmentation and connectivity modelling using GIS&T (grant from <a href="https://www.ncn.gov.pl/?language=en">the National Science Center - Poland</a>, 2012-2015, no. 2011/03/D/ST10/05568) [role: Principal Investigator]</h4>
<p>In the LIM project, we focused on developing new models and measures that enabled the quantitative description of fragmentation and connectivity. Our work involved forests and protected species, including the brown bear and European bison. Throughout the analysis, we employed geographic information technology and spatial data, such as elevation models and satellite land cover maps, alongside various analytical modeling methods. We demonstrated that our workflows could be successfully applied in practical settings. For example, they were instrumental in guiding environmental conservation plans, which involved identifying biodiversity hotspots, preventing biodiversity loss, determining reintroduction sites for endangered species, and delimiting ecological corridors.</p>
<p></p>
<h4>FORECOM project: Forest cover changes in mountainous regions - drivers, trajectories and implications (grant from <a href="https://www.eda.admin.ch/countries/poland/en/home/international-cooperation.html">the Swiss Contribution </a>, 2012-2016, No. PSPB 008/2010) [role: Senior researcher]</h4>
<p></p>
<h4><a href="https://lcluc.umd.edu/projects/200-years-land-use-and-land-cover-changes-and-their-driving-forces-carpathian-basin-central">200 years</a> of land use and land cover changes and their driving forces in the Carpathian basin in Central Europe (grant from <a href="https://lcluc.umd.edu/">the NASA LCLUC program</a>, 2011-2014, No. NNH09DA001N) [role: Senior researcher]</h4>
<p></p>
<h4>Mountain.TRIP project: Mountain Sustainability: Transforming Research into Practice (grant from the EU: SEVENTH FRAMEWORK PROGRAMME Environment (including Climate Change), 2009-2011, No. FP7-ENV-2009-5.1.0.2) [role: Senior researcher]</h4>
<p></p>
<h4>Land cover and land use change in the Polish Carpathians (grant from the Polish Ministry of Science and Education, 2008-2010, No. NNH09DA001N) [role: Co-Principal Investigator]</h4>
<p></p>
<h4>Land use change in the period of political transformation and their relationship with natural and socio-economic conditions in the western part of the Beskidy Mountains (grant from the Polish Ministry of Science and Education, 2004-2007, No. NNH09DA001N) [role: Doctoral researcher]</h4>
<p></p>
<button><a href="#Projects">Running projects ...</a></button>
<p></p>
</article>
<!-- SOCPIX project -->
<article id="SOCPIX_project">
<h2 class="major">SOCPIX project</h2>
<h3>Socializing the pixel - detecting and understanding of changing land systems with remote sensing and social sciences</h3>
<span class="image main"><img src="images/image_socpix.jpg" alt="" /></span>
<p></p>
<h3>Background</h3>
<p>Land provides essential resources to society, including food, fuel, fibres and many other ecosystem services that support humans, regulate risks of natural hazards, or provide cultural and spiritual services. By using land, society modifies the provision of these services. Changes in land systems are main factors of global environmental change and have large consequences for the local environment and human well-being. Understanding and modelling complex land systems and land change trajectories, the enhanced human pressures on the earth’s limited land resources, as well as the increasingly complex drivers of those changes, have been key objectives for land change science or land system science (LSS).</p>
<p></p>
<h3>Project objectives</h3>
<p>The main objective of this project was to develop analytical approaches explaining the linkages between the major processes in land systems, i.e., land use intensification and expansion, land use displacement and land use transition within the telecoupling framework with a particular emphasis on the advantage of Earth observations (EO) and spatial data use. This aim will be achieved in a sequence of tasks focusing on different aspects of the emerging land use change of European (the Carpathians), and North American (the Rocky Mountains and Sierra Nevada) mountainous ranges over last five decades and its linkages with other regions.</p>
<p></p>
<p>We developed concepts and methodologies that explained:</p>
<ul type = "square">
<li>how to integrate remote sensing data needed in telecoupling frameworks with socioeconomic information on pixel level (PIXEL SOCIALIZATION),</li>
<li>how to accurately map and link land use intensification and expansion, land use displacement and land use transition using remote sensing and spatial data,</li>
<li>how land use changes are influenced by a complexity of drivers that transcend spatial, institutional and temporal scales,</li>
<li>how land use dynamics are organized by different actors to shape land systems regime shifts and frontier emergence.</li>
</ul>
<p></p>
<h3>Team</h3>
<p>Katarzyna Ostapowicz (Principal Investigator)</p>
<p></p>
<h3>Collaboration</h3>
<p><a href="https://luclab.berkeley.edu/staff/van-butsic/"><b>Van Butsic</b></a> <a href="https://luclab.berkeley.edu/about/">LUC Lab</a>, <a href="https://ourenvironment.berkeley.edu/">Department of Environmental Science, Policy, and Management</a>, <a href="https://www.berkeley.edu/">University of California, Berkeley</a></p>
<p></p>
<h3>Acknowledgment</h3>
Grant from <a href="https://nawa.gov.pl/en/nawa">the Polish National Agency for Academic Exchange</a> (no.PPN/BEK/2018/1/00310/00001)</p>
<p></p>
<button><a href="#Completed_projects">Completed projects ...</a></button>
<p></p>
</article>
<!-- RS4FOR project -->
<article id="RS4FOR_project">
<h2 class="major">RS4FOR project</h2>
<h3>Forest change detection and monitoring using passive and active remote sensing data</h3>
<span class="image main"><img src="images/image_rs4for.jpg" alt="" /></span>
<p></p>
<h3>Background</h3>
<p>The RS4FOR project is situated within the critical field of environmental monitoring, specifically focusing on forest ecosystems. Leveraging advanced remote sensing technologies, the project aimed to enhance the accuracy and efficiency of detecting and monitoring changes in forest cover. Our study area was the picturesque yet ecologically sensitive Polish Carpathians, a region exemplifying temperate forests in mountainous terrains. By integrating a range of both passive and active remote sensing data sources, including optical and radar imagery along with airborne laser scanning, the project addressed pivotal concerns about forest health and sustainability.</p>
<p></p>
<h3>Aim & objectives</h3>
<p>The primary aim of the RS4FOR project was to develop and refine methodologies for improved forest cover change detection and monitoring. This was accomplished through the analysis of extensive Earth Observation datasets spanning several decades:</p>
<ul type = "square">
<li><b>Optical imagery:</b> Utilized time-series data from Landsat MSS, TM, ETM+, and OLI (1978-2020), along with Sentinel-2 (2016-2020),,</li>
<li><b>Radar imagery:</b> Analyzed using Sentinel-1 data collected from 2016 to 2020.</li>
<li><b>Airborne laser scanning (ALS:)</b> Data from the 2013 ISOK project was employed to enhance three-dimensional forest structure analysis.</li>
</ul>
These objectives were pursued with a focus on four key aspects of forest monitoring: forest cover and its dynamics, predictive models of forest structure changes, forest health assessment, and the conservation status of old-growth forests.</p>
<p></p>
<p>The RS4FOR project achieved significant advancements in the field of remote sensing applied to forest monitoring. Our integrated approach allowed for: </br>
<ul type = "square">
<li><b>Enhanced Detection and Monitoring:</b> Improved methodologies for detecting both forest cover conversions and modifications, even in the complex mountainous terrains of the Carpathians.</li>
<li><b>Predictive Modeling:</b> Development of robust models predicting changes in forest structure, aiding in proactive management and conservation efforts.</li>
<li><b>Forest Health Insights:</b> Advanced assessments of forest health, enabling timely interventions to mitigate disease or degradation.</li>
<li><b>Conservation of Old-growth Forests:</b> Critical insights into the status and dynamics of old-growth forests, contributing to their preservation.</li>
</ul>
The findings and methodologies developed in the RS4FOR project not only enhance our understanding of forest dynamics but also equip policymakers and conservationists with the tools necessary for effective forest management and protection.</p>
<p></p>
<h3>Publications</h3>
<p></p>
<p><b>Zielonka A.</b>, Drewnik M., Musielok Ł., Dyderski M. K., Struzik D., Smułek G., <b>Ostapowicz K.</b>, 2021, Biotic and Abiotic Determinants of Soil Organic Matter Stock and Fine Root Biomass in Mountain Area Temperate Forests—Examples from Cambisols under European Beech, Norway Spruce, and Silver Fir (Carpathians, Central Europe), <a href="https://www.mdpi.com/1999-4907/12/7/823">Forests, 12, 823</a> </p>
<p><b>Grabska E.</b>, Frantz D., <b>Ostapowicz K.</b>, 2020, Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians, <a href="https://www.sciencedirect.com/science/article/abs/pii/S0034425720304764?via%3Dihub">Remote Sensing of Environment, 251, 112103</a> </p>
<p><b>Grabska E.</b>, Hostert P., Pflugmacher D., <b>Ostapowicz K.</b>, 2019, Forest Stand Species Mapping Using the Sentinel-2 Time Series, <a href= "https://www.mdpi.com/2072-4292/11/10/1197">Remote Sensing, 11, 10, 1197</a></p>
<p></p>
<p>More coming soon by the end of 2024</p>
<p></p>
<h3>Team</h3>
<p>Katarzyna Ostapowicz (Principal Investigator)</br>
Katarzyna Staszyńska (Postdoctoral researcher)</br>
Ewa Grabska (Doctoral researcher)</br>
Anna Zielonka (Doctoral researcher)</p>
<p></p>
<h3>Collaboration</h3>
<p><b>Humboldt-Universitat zu Berlin, Geography Department, Earth Observation Lab., Germany</b></br>
Patrick Hostert</br>
Dirk Pflugmacher</br>
David Frantz</p>
<p></p>
<h3>Acknowledgment</h3>
Grant from <a href="https://www.ncn.gov.pl/?language=en">the National Science Center - Poland</a> (2016-2020, no.2015/19/B/ST10/02127)</p>
<p></p>
<button><a href="#Completed_projects">Completed projects...</a></button>
<p></p>
</article>
<!-- LIM project -->
<article id="LIM_project">
<h2 class="major">LIM project</h2>
<h3>Integration of categorical- and gradient-based approaches in landscape fragmentation and connectivity modelling using GIS&T</h3>
<span class="image main"><img src="images/image_lim.jpg" alt="" /></span>
<p></p>
<h3>Background</h3>
<p>The world around us is changing more and more heavily influenced by human activity. We transform the landscape around us and thereby change the conditions of existence of different species and their habitats. For example, forests fragmentation is shifting which influences connectivity of forest patches and affects animals’ movement. Therefore, for efficient spatial management or development of effective conservation mechanisms, it is essential to have the right tools and workflows that allow for complex evaluation of fragmentation and connectivity at the landscape and species level.</p>
<p></p>
<h3>Project aim & objectives</h3>
<p>In LIM project, we focused on new models and measures development which would enable quantitatively describe habitats’ fragmentation and connectivity. We worked with two protected species; brown bear and European bison. </p>
<p></p>
<h3>Outcomes</h3>
<p>At each step of the analysis, we used geographic information technology, among others, spatial data such as elevation models or satellite land cover maps and various analytical modelling methods e.g., network analysis. We have shown that our workflows can be successfully used in practice, e.g., to identify new directions in environment conservation plans that include identification of biodiversity hotspots and prevention of biodiversity loss, the location of reintroduction sites for endangered species or delimitation of ecological corridors. </p>
<p></p>
<h3>Publications</h3>
<p></p>
<p><b>Ziółkowska E.</b>, <b>Ostapowicz K.</b>, Radeloff V.C., Selva N., Kuemmerle T., Śmietana W., 2016, Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians, <a href="https://link.springer.com/article/10.1007/s10980-016-0368-8">Landscape Ecology, 31, 1863-1882</a></p>
<p><b>Ziółkowska E.</b>, Perzanowski K., Bleyhl B., <b>Ostapowicz K.</b>, Kuemmerle T., 2016, Understanding unexpected reintroduction outcomes: why do European bison do not colonize suitable habitat in the Carpathians? <a href="https://www.sciencedirect.com/science/article/abs/pii/S0006320715302111">Biological Conservation, 195, 106-117</a></p>
<p><b>Ziółkowska E.</b>, <b>Ostapowicz K.</b>, Kuemmerle T., Radeloff V., 2014, Effects of different matrix representations and connectivity measures on habitat network assessments, <a href="https://link.springer.com/article/10.1007/s10980-014-0075-2">Landscape Ecology, 29, 9, 1551-1570</a></p>
<p></p>
<h3>Team</h3>
<p>Katarzyna Ostapowicz (Principal Investigator)</br>
Elżbieta Ziółkowska (Doctoral researcher)</p>
<p></p>
<h3>Collaboration</h3>
<p><b>Humboldt-Universitat zu Berlin, Geography Department, Biogeography Lab., Germany</b></br>
Tobias Kummerle</br>
Benjamin Bleyhl</p>
<p><b>University of Wisconsin-Madison, Department of Forest and Wildlife Ecology, SILVIS Lab., USA</b></br>
Volker C. Radeloff</p>
<p><b>Polish Academy of Science, Poland</b></br>
Nuria Selva</br>
Kajetan Perzanowski</p>
<p></p>
<h3>Acknowledgment</h3>
Grant from <a href="https://www.ncn.gov.pl/?language=en">National Science Center - Poland</a> (2012-2015, no.2011/03/D/ST10/05568)</p>
<p></p>
<button><a href="#Completed_projects">Completed projects...</a></button>
<p></p>
</article>
<!-- Publications -->
<article id="Publications">
<h3><a href="#About">Katarzyna Ostapowicz</a></h3>
<h2 class="major">Publications</h2>
<span class="image main"><img src="images/image_publications_1.jpg" alt="" /></span>
<p></p>
<p><b>Mapping roadless areas in regions with contrasting human footprint</b></br>
In an increasingly human- and road-dominated world, the preservation of functional ecosystems has become highly relevant. While the negative ecological impacts of roads on ecosystems are numerous and well documented, roadless areas have been proposed as proxy for functional ecosystems. However, their potential remains underexplored, partly due to the incomplete mapping of roads. We assessed the accuracy of roadless areas identification using freely available road-data in two regions with contrasting levels of anthropogenic influence: boreal Canada and temperate Central Europe (Poland, Slovakia, Czechia, and Hungary). Within randomly selected circular plots (per region and country), we visually examined the completeness of road mapping using OpenStreetMap 2020 and assessed whether human influences affect mapping quality using four variables. In boreal Canada, roads were completely mapped in 3% of the plots, compared to 40% in Central Europe. Lower Human Footprint Index and road density values were related to greater incompleteness in road mapping. Roadless areas, defined as areas at least 1 km away from any road, covered 85% of the surface in boreal Canada (mean size ± s.d. = 272 ± 12,197 km2), compared to only 0.4% in temperate Central Europe (mean size ± s.d. = 0.6 ± 3.1 km2). By visually interpreting and manually adding unmapped roads in 30 randomly selected roadless areas from each study country, we observed a similar reduction in roadless surface in both Canada and Central Europe (27% vs 28%) when all roads were included. This study highlights the urgent need for improved road mapping techniques to support research on roadless areas as conservation targets and surrogates of functional ecosystems.</br>
<b>Hoffmann M.T., <b>Ostapowicz K.</b>, Bartoń K., Ibisch P.L., Selva N., 2024, Scientific Reports, 14, 4722</b></br>
<button><a href="https://www.nature.com/articles/s41598-024-55283-3"><small>PDF</small></a></button> <button><a href="#TRACE_project"><small>TRACE project</small></a></button>
<p></p>
<p><b>The northernmost hyperspectral FLoX sensor dataset for monitoring of high-Arctic tundra vegetation phenology and Sun-Induced Fluorescence (SIF)</b></br>
Information about forest stand species distribution is essential for biodiversity modelling, forest disturbances, fire hazard and drought monitoring, biomass and carbon estimation, detection of non-native and invasive species, as well as for planning forest management strategies. High temporal and spectral resolution remote sensing data from the Sentinel-2 mission enables the derivation of accurate and timely maps of tree species in forests in a cost-efficient way. However, there is still a lack of studies regarding forest stand species mapping for large areas like the Polish Carpathian Mountains (approx. 20,000 km2). In this study, we aimed to develop a workflow to obtain forest stand species maps with machine learning algorithms applied to multi-temporal Sentinel-2 products and environmental data at regional scale. Using variable importance techniques - Variable Importance Using Random Forests (VSURF) and Recursive Feature Elimination (RFE) - we assessed three Sentinel-2 Best Available Pixel composites (April, July and October), eight annual spectral-temporal metrics (STM; mean, minimum, maximum, standard deviation, range, first quartile, third quartile and interquartile range), and four environmental topographic variables (elevation, slope, aspect, distance to water bodies), i.e. 114 variables in total. Following a variable importance assessment, we produced maps of eleven tree species with the use of three Machine Learning algorithms: Random Forest (RF), Support Vector Machines (SVM) and Extreme Gradient Boosting (XGB) on nine different variable subsets, i.e. in total 27 classifications. The results showed that SVM outperformed the other two classifiers - the highest overall accuracy exceeded 85% for SVM classification of all variables (86.9%), and 64 variables (85.6%). Including elevation information improved the accuracies. From the best five classifications we created a final ensemble map (overall accuracy of 86.6%) and a precision map based on the Simpson Index, which indicates where the five models agree. This ensemble approach allowed us to determine that the lowest precision occurred in foothills and basins with lower forest cover, in the areas with lack of good quality imagery, and at the borders of stands with homogenous species composition. On the other hand, the highest precision occurred in regions with homogenous stands with high forest and canopy cover. The study demonstrates the potential of Sentinel-2 imagery and topographic data in mapping forest stand species in large mountainous areas with high accuracy. Furthermore, it demonstrates the usefulness of the ensemble approach, which enables to assess the classification precision.</br>
<b>Tømmervik H., Julitta T., Nilsen L.; Park T., Burkart A., <b>Ostapowicz K.</b>, Karlsen S.R., Parmentier F., Pirk N., Bjerke J.W., 2023, Data in Brief, 50, 109581</b></br>
<button><a href="https://www.sciencedirect.com/science/article/pii/S2352340923006807?via%3Dihub"><small>PDF</small></a></button>
<p></p>
<p><b>Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians</b></br>
Information about forest stand species distribution is essential for biodiversity modelling, forest disturbances, fire hazard and drought monitoring, biomass and carbon estimation, detection of non-native and invasive species, as well as for planning forest management strategies. High temporal and spectral resolution remote sensing data from the Sentinel-2 mission enables the derivation of accurate and timely maps of tree species in forests in a cost-efficient way. However, there is still a lack of studies regarding forest stand species mapping for large areas like the Polish Carpathian Mountains (approx. 20,000 km2). In this study, we aimed to develop a workflow to obtain forest stand species maps with machine learning algorithms applied to multi-temporal Sentinel-2 products and environmental data at regional scale. Using variable importance techniques - Variable Importance Using Random Forests (VSURF) and Recursive Feature Elimination (RFE) - we assessed three Sentinel-2 Best Available Pixel composites (April, July and October), eight annual spectral-temporal metrics (STM; mean, minimum, maximum, standard deviation, range, first quartile, third quartile and interquartile range), and four environmental topographic variables (elevation, slope, aspect, distance to water bodies), i.e. 114 variables in total. Following a variable importance assessment, we produced maps of eleven tree species with the use of three Machine Learning algorithms: Random Forest (RF), Support Vector Machines (SVM) and Extreme Gradient Boosting (XGB) on nine different variable subsets, i.e. in total 27 classifications. The results showed that SVM outperformed the other two classifiers - the highest overall accuracy exceeded 85% for SVM classification of all variables (86.9%), and 64 variables (85.6%). Including elevation information improved the accuracies. From the best five classifications we created a final ensemble map (overall accuracy of 86.6%) and a precision map based on the Simpson Index, which indicates where the five models agree. This ensemble approach allowed us to determine that the lowest precision occurred in foothills and basins with lower forest cover, in the areas with lack of good quality imagery, and at the borders of stands with homogenous species composition. On the other hand, the highest precision occurred in regions with homogenous stands with high forest and canopy cover. The study demonstrates the potential of Sentinel-2 imagery and topographic data in mapping forest stand species in large mountainous areas with high accuracy. Furthermore, it demonstrates the usefulness of the ensemble approach, which enables to assess the classification precision.</br>
<b>Grabska E., Frantz D., <b>Ostapowicz K.</b>, 2020, Remote Sensing of Environment, 251, 112103</b></br>
<button><a href="https://www.sciencedirect.com/science/article/abs/pii/S0034425720304764?via%3Dihub"><small>PDF</small></a></button> <button><a href="#RS4FOR_project"><small>RS4FOR project</small></a></button>
<p></p>
<button><a href="https://orcid.org/0000-0002-4830-8202">More publications...</a></button>
<p></p>
</article>
<!-- Contact -->
<article id="Contact">
<h3><a href="#About">Katarzyna Ostapowicz</a></h3>
<h2 class="major">Contact</h2>
<span class="image main"><img src="images/image_contact_1.jpg" alt="" /></span>
<p></p>
<p><b>Postal and office address:</b> <a href="https://www.nina.no/english/About-NINA/Contact/Employees/Employee-info?AnsattID=16669"><b>Norwegian Institute for Nature Research NINA</b></a>, FRAM – High North Research Centre for Climate and the Environment, PO Box 6606 Langnes, NO-9296 Tromsø, Norway <br/>
<b>Phone:</b> +47 46505709</br>
<b>Email:</b> katarzyna.ostapowicz@nina.no</p>
<p></p>
<ul class="icons">
<li><a href="https://github.com/kasiaostapowicz" class="icon brands fa-github"><span class="label">GitHub</span></a></li>
<li><a href="mailto:katarzyna.ostapowicz@nina.no" class="icon fa-envelope"><span class="label">Email</span></a></li>
</ul>
</article>
</div>
<!-- Footer -->
<footer id="footer">
<p class="copyright">© Katarzyna Ostapowicz 2024. Powered by <a href="https://html5up.net/dimension">the Dimension theme</a> for <a href="https://html5up.net">HTML5 UP</a>. Images: Katarzyna Ostapowicz.</p>
</footer>
</div>
<!-- BG -->
<div id="bg">
<!-- Scripts -->
<script src="assets/js/jquery.min.js"></script>
<script src="assets/js/browser.min.js"></script>
<script src="assets/js/breakpoints.min.js"></script>
<script src="assets/js/util.js"></script>
<script src="assets/js/main.js"></script>
</body>
</html>